Bill Gurley warns AI boom is setting up a bubble and a coming “reset”
Benchmark’s Gurley points to get-rich-quick dynamics, heavy AI cash burn, and a potential entry point in beaten-down software stocks
Benchmark general partner Bill Gurley said March 16 that the artificial intelligence wave has made “a lot of people” rich quickly and that he expects a “reset” to come. He argued that bubble dynamics follow fast wealth creation, even when the underlying technology shift is real.
Gurley’s comments land as public-market software names have been under pressure while the largest tech platforms accelerate AI infrastructure spending. The setup matters for crypto traders because the same risk-on liquidity and narrative momentum that has powered AI-linked equities has also shaped flows into high-beta digital assets, especially tokens tied to compute, data, and infrastructure themes.
Speaking on CNBC’s “Money Movers,” Gurley framed the current moment as a familiar cycle: rapid gains attract copycats, and that crowding can end in a repricing. “When people get rich quick, a whole bunch of people come in and want to get rich too, and that's why we end up with bubbles ,” he said.
He also pushed back on the idea that a bubble implies the underlying shift is fake. Gurley referenced the work of economic scholar Carlota Perez and her book “Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages.” In that framework, he said, “bubbles only exist when the actual wave is real.”
Gurley tied the prospective reset to positioning and valuation discipline rather than a call to abandon the theme. He said that when the reset happens, investors should have a price in mind for beat-down software-as-a-service stocks “and start gobbling them up.”
Recent performance in the software complex has been weak in 2026. Salesforce and ServiceNow have each lost about 25% so far this year, while the iShares Expanded Tech-Software Sector ETF (IGV), which generally tracks the sector, is down about 20%.
At the same time, spending tied to AI buildouts has climbed. Tech companies are spending at record rates due to massive investments in AI infrastructure and soaring memory costs, with AI spending for Amazon, Meta, Google and Microsoft projected to be about $700 billion this year.
Gurley contrasted today’s model-builders with his experience at Uber, where he said the company’s annual burn rate of $2 billion during his involvement was “high anxiety.” He described the much larger cash burn associated with leading AI companies as a risky operating posture. “God bless them,” he said of AI companies like Anthropic and OpenAI that are burning through cash. “It's a scary way to run a company.”
What remains unresolved is timing and magnitude: Gurley did not put a date on the “reset,” and the market’s next signal will likely come from whether AI infrastructure spending projections hold up alongside continued pressure in software valuations.
